Control of Atherosclerotic Risk Factors During the COVID-19 Pandemic in the U.S.

INTRODUCTION

Public health response to the COVID-19 pandemic led to widespread social and economic changes and disruption of health care delivery. During the pandemic, there was a reduction in primary care visits with a higher proportion of telemedicine encounters.1 Telemedicine visits were associated with lower new medication prescriptions and less frequent assessments of blood pressure and cholesterol levels.2,3

Lockdown restrictions coincided with an observed reduction in physical activity, weight gain, and increased rates of depression and anxiety.4‒9 Pandemic-related changes in cardiovascular risk factors and the 10-year predicted risk of atherosclerotic cardiovascular disease (ASCVD) were evaluated in adults within an integrated healthcare system in the U.S.

METHODS

The study included Kaiser Permanente Southern California (KPSC) members aged 40 to 79 years with lipid panel and blood pressure measurements pre-pandemic (March 19, 2019‒March 18, 2020) and another set of measurements after COVID-19 vaccines became available, more than 9 months into the pandemic (December 14, 2020‒December 13, 2021). KPSC is an integrated healthcare delivery system that provides comprehensive care, including outpatient, inpatient, and pharmaceutical benefits. Patients who were not KPSC members and those with established ASCVD (i.e., coronary artery disease, cerebral vascular disease, or peripheral vascular disease) were excluded. An individual's estimated 10-year ASCVD risk during each study period was calculated using the pooled cohort equation per guideline recommendations.10 The patient's age on March 19, 2020, was used for ASCVD risk estimation for both periods so that differences in ASCVD risk estimation reflect differences in risk factor control. The distribution of cardiovascular risk factors and ASCVD scores was assessed in the population pre-pandemic and during the pandemic.

Multivariable logistic regression modeling was performed to evaluate the association between baseline characteristics and a >10% increase in estimated ASCVD risk during the pandemic. Variables in the model included age, sex, race /ethnicity, income, hypertension, diabetes, smoking status, and BMI. ORs and 95% CIs were calculated. Analyses were performed with Stata 14 (Stata-Corp, College Station, TX). A 2-sided p<0.05 was used to define statistical significance. This study was approved by the IRB of KPSC with a waiver of informed consent.

RESULTS

Of 349,185 KPSC members with lipid and blood pressure information pre-pandemic and during the pandemic, the median age was 59 years (IQR=51‒66), 58.4% were women, 34.5% White, 8.7% Black, 16.7% Asian, and 36.6% Hispanic. During the pandemic, a higher proportion of individuals had uncontrolled hypertension ≥140 mmHg (17.1% vs 13.1%) and elevated cholesterol ≥240 mg/dL (10.8% vs 9.9%) (Table 1 ). At a population level, median estimated 10-year ASCVD risk increased from 6.0% (IQR=2.3%‒13.1%) pre-pandemic to 6.3% (IQR=2.5%‒13.5%) during the pandemic, and a higher proportion of individuals were categorized as having high (≥20%) ASCVD risk (13.9% vs 13.0%). Subgroup analysis of patients treated with statins or hypertension medications showed similar findings. Among patients on hypertension medications, 23.6% had uncontrolled hypertension ≥140 mmHg during the pandemic compared to 20.1% pre-pandemic. Among those on statin and hypertension medications, the difference was 22.9% during the pandemic and 17.8% pre- pandemic.

Table 1

Cardiovascular Risk Factors and Estimated 10-Year ASCVD Risk Before and During the COVID-19 Pandemic (n=349,185)

ASCVD risk and risk factors	Pre-pandemic(March 2019 to March 2020)	Pandemic(December 2020 to December 2021)	p-valuea
ASCVD 10-year predicted riskb
Median (IQR), %	6.0 (2.3‒13.1)	6.3 (2.5‒13.5)	<0.001
<5%	154,547 (44.3)	150,753 (43.2)	<0.001
5% to <7.5%	44,134 (12.6)	43,945 (12.6)
≥7.5% to <20%	105,274 (30.1)	106,065 (30.4)
≥20%	45,230 (13.0)	48,422 (13.9)
SBP, mmHg
Median (IQR)	127 (117‒135)	129 (119‒137)	<0.001
<120	106,859 (30.6)	91,667 (26.3)	<0.001
120 to <130	94,034 (26.9)	90,654 (26.0)
130 to <140	102,746 (29.4)	107,352 (30.7)
140 to <160	37,309 (10.7)	47,782 (13.6)
≥160	8,237 (2.4)	12,030 (3.5)
DBP, mmHg
Median (IQR)	74 (67‒80)	74 (67‒81)	<0.001
<80	253,789 (72.7)	246,334 (70.6)	<0.001
80 to <90	76,344 (21.9)	80,638 (23.1)
90 to <100	15,320 (4.4)	17,711 (5.1)
≥100	3,732 (1.1)	4,502 (1.3)
Cholesterol, mg/dL
Median (IQR)	184 (157‒213)	184 (155‒214)	<0.001
<200	223,814 (64.1)	221,817 (63.5)	<0.001
200‒239	90,635 (26.0)	89,515 (25.6)
≥240	34,736 (9.9)	37,853 (10.8)
HDL, mg/dL
Median (IQR)	50 (42‒61)	51 (43‒61)	<0.001
<40	60,324 (17.3)	58,266 (16.7)	<0.001
40 to <60	192,724 (55.2)	190,680 (54.6)
≥60	96,137 (27.5)	100,239 (28.7)
LDL, mg/dL
Median (IQR)	108 (84‒133)	106 (80‒132)	<0.001
<70	47,177 (13.5)	56,038 (16.1)	<0.001
70 to <100	95,810 (27.4)	96,045 (27.5)
100 to <130	108,817 (31.2)	101,810 (29.2)
130 to <160	67,505 (19.3)	65,138 (18.7)
160 to <190	23,064 (6.6)	23,342 (6.7)
≥190	6,812 (2.0)	6,811 (2.0)
Triglyceride, mg/dL
Median (IQR)	118 (84‒169)	121 (86‒173)	<0.001
<150	224,540 (67.1)	218,508 (65.5)	<0.001
150 to <200	54,888 (16.4)	56,264 (16.9)
200 to <500	53,290 (15.9)	56,680 (17.0)
≥500	1,953 (0.6)	1,935 (0.6)
Smoking statusc
Never	253,132 (72.5)	251,786 (72.1)	<0.001
Quit	79,165 (22.7)	82,056 (23.5)	<0.001
Passive	1,291 (0.4)	1,264 (0.4)
Active	15,481 (4.4)	13,963 (4.0)
Missing	116 (0.03)	116 (0.06)
Hypertension treatment
Yes	151,373 (43.4)	162,667 (46.6)	<0.001
No	197,812 (56.6)	186,518 (53.4)
Statin
Yes	131,592 (37.7)	147,222 (42.2)	<0.001
No	217,593 (62.3)	201,963 (57.8)
HgbA1c level, %	n=327611	n=334272
Median (IQR)	5.7 (5.5‒6.1)	5.7 (5.5‒6.2)	<0.001
<5.7	170,925 (52.2)	169,078 (50.6)	<0.001
5.7 to <6.5	97,337 (29.7)	99,897 (29.9)
6.5 to <8.5	44,042 (13.4)	47,825 (14.3)
≥8.5	15,307 (4.7)	17,472 (5.2)
BMI, kg/m2	n=346,353	n=338,100
Median (IQR)	28.6 (25.2‒32.9)	28.6 (25.1‒32.9)	<0.001
<18.5	2,151 (0.6)	2,526 (0.8)	<0.001
18.5 to 24.9	80,317 (23.2)	78,775 (23.3)
25.0 to 29.9	124,355 (35.9)	120,380 (35.6)
30.0 to 39.9	116,481 (33.6)	113,384 (33.5)
≥40.0	23,049 (6.7)	23,035 (6.8)

Note: Boldface indicates statistical significance (p<0.05).

Wilcoxon matched-pairs signed-rank test or Student's t-test for continuous variables and Pearson's chi-squared for categorical variables.

Estimated 10-year ASCVD risk during each study period was calculated using the pooled cohort equation as per American Heart Association and American College of Cardiology guideline recommendations. The patient's age on March 19, 2020, was used for calculation for both the pre-pandemic period and the pandemic period.

Self-reported smoking status from the electronic health record.

ASCVD, atherosclerotic cardiovascular risk; SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL, high density lipoprotein; LDL, low-density lipoprotein.

During the pandemic, 6,792 (1.9%) individuals had a >10% increase in their estimated ASCVD risk. Factors associated with increased odds of having >10% increase in ASCVD risk included older age (OR=3.5, 95% CI=3.4, 3.6, for each decade increase), male sex (OR=1.8, 95% CI=1.7, 1.9), Black race (OR=2.2, 95% CI=2.0, 2.4), and low income <$45,000 per year (OR=1.3, 95% CI=1.2, 1.4).

DISCUSSION

In this racially and ethnically diverse population in southern California, the COVID-19 pandemic was associated with a higher proportion of individuals with uncontrolled blood pressure and cholesterol than in the pre-pandemic period, despite increased treatment attempts. Suboptimal risk factor control resulted in a statistically significant increase in their estimated 10-year ASCVD risk. Individuals who were older, Black, or with low-income were disproportionately affected. Targeted efforts to improve cardiovascular risk factor management, such as through programs to improve hypertension control in vulnerable populations, will be important to ensure improved cardiovascular health outcomes in the coming years.

Limitations

Limitations of this study include the observational design and inclusion of only those with lipids and blood pressure measurements. Findings from this well-insured population may not be generalizable to those without insurance.

CONCLUSIONS

During the COVID-19 pandemic, widespread disruptions of healthcare delivery was associated with an increased proportion of individuals with sub-optimally controlled cardiovascular risk factors. As hospitals and clinics resume normal services, special attention should be paid to the evaluation and treatment of cardiovascular risk factors.

Credit Author Statement

Ming-Sum Lee: conceptualization, writing – original draft, project administration, methodology, analysis; Aiyu Chen: data curation, methodology, analysis, writing – review and editing; John Herald: writing – review and editing; Rohith Nayak: writing – review and editing; Yuh-Jer Albert Shen: writing – review and editing.

ACKNOWLEDGMENTS

No financial disclosures were reported by the authors of this paper.

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